12 citations · 13 across the 9 of their papers we have counts for
10 papers
Deep Learning Based Domain Adaptation Methods in Remote Sensing: A Comprehensive Survey
Shuchang Lyu, Qi Zhao, Zheng Zhou +6
Domain adaptation is a crucial and increasingly important task in remote sensing, aiming to transfer knowledge from a source domain a differently distributed target domain. It has…
Adversarial Versus Federated: An Adversarial Learning based Multi-Modality Cross-Domain Federated Medical Segmentation
You Zhou, Lijiang Chen, Shuchang Lyu +7
Federated learning enables collaborative training of machine learning models among different clients while ensuring data privacy, emerging as the mainstream for breaking data silos…
ViTaL: A Multimodality Dataset and Benchmark for Multi-pathological Ovarian Tumor Recognition
You Zhou, Lijiang Chen, Guangxia Cui +5
Ovarian tumor, as a common gynecological disease, can rapidly deteriorate into serious health crises when undetected early, thus posing significant threats to the health of women.…
ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation
Muyi Bao, Shuchang Lyu, Zhaoyang Xu +4
Skin lesion segmentation is a critical challenge in computer vision, and it is essential to separate pathological features from healthy skin for diagnostics accurately. Traditional…
Joint-Optimized Unsupervised Adversarial Domain Adaptation in Remote Sensing Segmentation with Prompted Foundation Model
Shuchang Lyu, Qi Zhao, Guangliang Cheng +4
Unsupervised Domain Adaptation for Remote Sensing Semantic Segmentation (UDA-RSSeg) addresses the challenge of adapting a model trained on source domain data to target domain sampl…
BEARD: Benchmarking the Adversarial Robustness for Dataset Distillation
Zheng Zhou, Wenquan Feng, Shuchang Lyu +3
Dataset Distillation (DD) is an emerging technique that compresses large-scale datasets into significantly smaller synthesized datasets while preserving high test performance and e…
OVGNet: A Unified Visual-Linguistic Framework for Open-Vocabulary Robotic Grasping
Li Meng, Zhao Qi, Lyu Shuchang +4
Recognizing and grasping novel-category objects remains a crucial yet challenging problem in real-world robotic applications. Despite its significance, limited research has been co…
BACON: Bayesian Optimal Condensation Framework for Dataset Distillation
Zheng Zhou, Hongbo Zhao, Guangliang Cheng +4
Dataset Distillation (DD) aims to distill knowledge from extensive datasets into more compact ones while preserving performance on the test set, thereby reducing storage costs and…
OV-VG: A Benchmark for Open-Vocabulary Visual Grounding
Chunlei Wang, Wenquan Feng, Xiangtai Li +5
Open-vocabulary learning has emerged as a cutting-edge research area, particularly in light of the widespread adoption of vision-based foundational models. Its primary objective is…
MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation
Qi Zhao, Shuchang Lyu, Wenpei Bai +7
Ovarian cancer is one of the most harmful gynecological diseases. Detecting ovarian tumors in early stage with computer-aided techniques can efficiently decrease the mortality rate…